Innovative Algorithms for VISSIM Microsimulation Calibration and Traffic Breakdown Modeling at On-Ramp Bottlenecks

On-ramp merging areas are critical points in expressway operations, often prone to traffic breakdowns that disrupt traffic flow and exacerbate congestion. Microscopic simulation tools like VISSIM are essential for transportation planners, but their effectiveness hinges on accurately replicating both microscopic and macroscopic traffic dynamics. This study introduces two innovative algorithms to enhance VISSIM’s reliability in modeling traffic breakdowns. The first algorithm presents a novel methodology for calibrating the Wiedemann-99 car-following parameters, ensuring alignment between observed and simulated vehicle trajectories and achieving accurate replication of both microscopic behavior and macroscopic measures. The second algorithm calculates breakdown probabilities based on the Wiedemann model without requiring extensive time-series speed data, offering a practical solution for data-limited regions. The methodology was validated using real-world trajectory data from 1477 mainline and 769 on-ramp vehicles across six sites in Tehran, Iran. The results demonstrated that the calibrated model outperformed the default parameter settings in replicating breakdown probabilities, even when using the unseen dataset for CC parameter calibration, highlighting the robustness of the proposed approach. This research provides a practical framework for improving congestion mitigation strategies, particularly in regions with constrained access to detailed traffic data.